Lab Reflection
1a.) Questions:
- How has the United States military influenced the lifestyle of undergraduate students at the University of Illinois at Urbana-Champaign?
- What impact has the United States federal government made on the University of Illinois at Urbana-Champaign?
In order to answer these questions, I will use the University of Illinois at Urbana-Champaign digital library. The digital library will allow me to access important documents related to my question while maintaining the social distancing recommended by the CDC. I will use terms such as “war”, “military”, “military service”, and “World War I” to collect this data.
1b.) 4 Screenshots:
Source: https://digital.library.illinois.edu/items/b7892ff0-7ee5-0135-017e-0050569601ca-d
Source: https://archon.library.illinois.edu/index.php?p=digitallibrary/digitalcontent&id=11064
Source: https://archon.library.illinois.edu/index.php?p=digitallibrary/digitalcontent&id=6064
Source: https://archon.library.illinois.edu/index.php?p=digitallibrary/digitalcontent&id=993
1c.) Line of Inquiry
To answer this question, I will continue to research through these databases. I will also look into interviewing my fellow undergraduates who are currently in ROTC and other military programs at the University of Illinois at Urbana-Champaign. I could also collect data from undergraduates at ROTC.
Reading Response
Andrew Yang discusses the term “normal” in these chapters as the average. However, this term could be interpreted differently depending on the person. He felt embarrassed about his struggles and setbacks when he heard about the struggles of his Uber driver. For the first example of data, Andrew Yang uses information about the educational attainment of people in the United States. The source of this information was provided by the U.S. Census Bureau. He organizes the data by gender and race. This creates a divide in averages in men and women. There is also a divide in education among Whites, Blacks, Asians, and Hispanics. Andrew continues the divisions in education by organizing the incomes by education attainment. These education attainments show a divide in income among Americans.
The next set of data and statistics that Andrew Yang discusses is the largest occupational groups in the United States. The total number of workers in the United States is around 140 million according to the Bureau of Labor Statistics. He uses another source from the government which promotes the credibility of the data that he is presenting. Andrew Yang assumes that retail workers don’t have degrees. There is some truth to this claim, however, there is no direct statistic regarding the actual educational attainment. Another problem with this retail section is his manipulation of data. Mr. Yang uses the average salary of retail workers which is $22,900. He then uses the median age of the workers which is 39 years old. I do not have the average age of retail workers but the data would not be as alarming to readers if the average had a lower age then the median. He used the median data to emphasize the divide among working-class Americans.
The third piece of data and statistics discusses truck drivers in the United States. Mr. Yang states that truck driving is the most popular job in 29 of the 50 states. He then discusses the growing automatization of trucks. Andrew Yang that labor costs and fewer accidents would destroy this job market. He also explains that Elon Musk’s Teslas are self-driving. From my experience riding in a Tesla, the self-driving is not complete by itself. Sometimes the automation could turn off and require the driver to take control of the car. This could create the argument that self-driving trucks and cars are more dangerous than the current vehicles we drive today. However, the trial and error that comes with automation could make self-driving cars inevitable. Overall, Andrew Yang sums up the potential decline of truck drivers in the United States.
Hi Goose, I think you wrote an excellent post. I think that using the digital library in reference to your questions about the military and the University of Illinois will benefit you a lot. Additionally, Yang’s first set of data in your reading response relates to mine on how he organizes data by race and gender. To add to your point, the unequal distribution can be clearly seen after observing the different percentages of incomes between the different races and genders of Americans provided by the U.S Census Bureau.
Great to hear about how you pointed out that the average could be lower than the median, due to it being skewed left. I hadn’t thought about the statistics so rigorously as that. I thought it was interesting that you specifically pointed out the Uber driver story — I feel like what’s instrumental to the success of his points is how he sets them up by appealing to the pathos of his readers beforehand with stories like that that further show the difference in lives.